Abstract: A radio node that selectively performs a remedial action is described. During operation, the radio node detects a potential change in a location of the radio node relative to a predefined location. For example, the radio node may detect the potential change in the location based at least in part on a change in a network parameter of the radio node and/or by performing a scan of wireless signals in an environment of the radio node. Then, in response to detecting the potential change in the location, the radio node determines the location of the radio node (e.g., by using a positioning system). When there is at least a predefined change in the location of the radio node relative to the predefined location, the radio node selectively performs the remedial action. Notably, the remedial action may include: providing an alert or a notification, discontinuing transmissions, or re-register the radio node.

Abstract: During operation, a radio node may provide, at a transmit time during a first time interval, a first instance of a keep-alive message to a computer. Then, the radio node may receive, at a receive time prior to a first instance of a transmit expire time, an instance of a keep-alive response from the computer, where the instance of the keep-alive response authorizes the radio node to transmit in a granted portion of the spectrum until a second instance of the transmit expire time has elapsed. Moreover, the radio node may determine, based at least in part on the receive time and the first instance of the transmit expire time, an updated transmit time. Next, the radio node may provide, at the updated transmit time, which is prior to the second instance of the transmit expire time, a second instance of the keep-alive message addressed to the computer.

Abstract: During operation, a radio node may receive location information relating to a location of the radio node. Then, the radio node may provide a grant request to a computer, where the grant request includes a request to reserve a portion of a shared-license-access band of frequencies for use by the radio node based at least in part on the location information. Note that the location information may indicate whether the radio node is included in a geographic region. For example, the geographic region may include locations within a predefined distance from a boundary, such as a coastline. When the location information indicates the radio node is included in the geographic region, the portion of the shared-license-access band of frequencies may be outside of a second portion of the shared-license-access band of frequencies that is selectively used by a government user or a satellite service.

Abstract: During operation, a radio node may receive, from a computer, approval and authorization to use a first grant for a first portion of an SLA band of frequencies, and approval and authorization to use a second grant for a second portion of the SLA band of frequencies, where the first grant is a primary grant and the second grant is a secondary grant in a supplemental downlink carrier aggregation. Then, the interface circuit may receive, from the computer, a heartbeat response that includes a grant termination message for the first grant, where the grant termination message includes a warning that indicates that the use of the first portion of the SLA band of frequencies is revoked after a time interval. In response to the grant termination message, the interface circuit may define the second grant as the primary grant for the supplemental downlink carrier aggregation.

Abstract: During operation, a radio node may determine a desired bandwidth in a shared-license-access band of frequencies. Then, the radio node may identify two or more sub-spectra based at least in part on the desired bandwidth, where a sum of ranges of frequencies in the sub-spectra equals the desired bandwidth, and a given sub-spectra includes a range of frequencies. Next, the radio node may provide, to the computer, grant requests for the sub-spectra, where a given grant request includes a request to reserve a given one of the sub-spectra for use by the radio node, and a probability of approval of the given grant request is larger than a probability of a grant request for the desired bandwidth. Note that at least two of the sub-spectra may be separated by an intervening band of frequencies (i.e., at least two of the sub-spectra may be non-contiguous).

Abstract: During operation, the radio node may identify a second portion of a shared-license-access (SLA) band of frequencies with an improved communication-performance metric relative to a first portion of the SLA band of frequencies, which is currently approved and authorized for use. In response, the radio may provide a grant request to the computer for the second portion of the SLA band of frequencies, and may receive a grant response from the computer with an approval for a grant to the second portion of the SLA band of frequencies. Then, the radio node may provide a heartbeat request to the computer requesting authorization to use the second portion of the SLA band of frequencies, and may receive a heartbeat response from the computer with the authorization. Next, the radio node may provide a relinquishment request to the computer for the first portion of the SLA band of frequencies.

Abstract: A method, a device, and a non-transitory storage medium are described in which a machine learning-based resource management service is provided. A network device obtains network and end device information, and uses machine learning to determine whether to adjust an auto-scaling rule pertaining to the provisioning of an application service. The network device generates a modified auto-scaling rule based on the analysis.

Abstract: Methods to separate or recover brine that is present in an invert emulsion are described. The brine is present as an internal phase in the invert emulsion. The brine can be a valuable component, such as an alkali metal formate, and separation and recovering of the brine from the invert emulsion permits the brine to be reused.

Abstract: A computer device may include a memory storing instructions and processor configured to execute the instructions to provide a test configuration to a plurality of multi-access edge computing (MEC) devices; collect test results associated with the provided test configuration from the plurality of MEC devices; and obtain capability information associated with particular ones of the plurality of MEC devices. The computer device may be further configured to generate a test report that relates one or more parameters included in the test results and the obtained capability information to particular ones of the plurality of MEC devices; and use the generated test report to select a MEC device from the plurality of MEC devices for a user equipment (UE) device requesting an application session.

Abstract: A method, a device, and a non-transitory storage medium are described in which a edge content distribution service is provided. The edge content distribution service may include the distribution of static content among multi-access edge computing networks. The edge content distribution service may include tiered overlay networks that are correlated to performance metrics associated with application services, static contents of the application services, and/or the acquisition and delivery of the static contents. The edge content distribution service also consider available network resources at the multi-access edge computer networks and the overlay networks of the tiered architecture.

Abstract: A device obtains previously created data content. The device unmasks and extracts one or more chain of custody blocks stored in association with the data content. The one or more chain of custody blocks includes chain of custody data identifying who, when, where, and, with what hardware and/or software, created or edited the data content. The device analyzes the one or more chain of custody blocks and validates an origination of the data content based on the analysis of the one or more chain of custody blocks.

Abstract: A method, a device, and a non-transitory storage medium are described in which a lifecycle management service is provided. A network device of an application service network may use the number of requests from end devices as a basis to determine whether to terminate a virtual network device. The network device may compare the number of requests to management information that includes a threshold number of requests value. The network device may also instantiate a virtual network device based on receipt of a domain name system request and radio network information.

Abstract: A method, a device, and a non-transitory storage medium are described in which a machine learning-based resource management service is provided. A network device obtains network and end device information, and uses machine learning to determine whether to adjust an auto-scaling rule pertaining to the provisioning of an application service. The network device generates a modified auto-scaling rule based on the analysis.

Abstract: A method, a device, and a non-transitory storage medium are described in which a machine learning-based resource management service is provided. A network device obtains network and end device information, and uses machine learning to determine whether to adjust an auto-scaling rule pertaining to the provisioning of an application service. The network device generates a modified auto-scaling rule based on the analysis.

Abstract: Embodiments of the present disclosure pertain to systems and method for extracting data from an image. In one embodiment, a method of extracting data from an image comprises receiving, from an optical character recognition (OCR) system, OCR text in response to sending an image to the OCR system. The OCR text comprises a plurality of lines of text. Each line of text is classified as either a line item or not a line item using a machine learning algorithm, and a plurality of data fields are extracted from each line of text classified as a line item.

Abstract: An exemplary edge compute orchestration system that is communicatively coupled with a set of edge compute nodes in a communication network accesses performance data aggregated by a particular edge compute node of the set. The performance data includes a performance metric and geolocation data detected by a user equipment (UE) device communicatively coupled to the communication network. The edge compute orchestration system integrates the performance data into a geolocation-indexed performance dataset representative of detected performance metrics, indexed by geolocation, for the communication network. Then, based on the geolocation-indexed performance dataset, the edge compute orchestration system selects the particular edge compute node for performance of an edge compute task. Corresponding systems and methods are also disclosed.

Abstract: A method, a device, and a non-transitory storage medium are described in which a lifecycle management service is provided. A network device of an application service network may use the number of requests from end devices as a basis to determine whether to terminate a virtual network device. The network device may compare the number of requests to management information that includes a threshold number of requests value. The network device may also instantiate a virtual network device based on receipt of a domain name system request and radio network information.

Abstract: Systems and methods provide a MEC policy optimization service. A network device applies, in a first edge cluster of the application service layer network, a policy for an application service that supports a customer application; receives network performance data related to execution of the application service; identifies, based on the network performance data, an improved policy to optimize the first policy for the customer application in the first edge cluster; and sends a model of the improved policy to a central network device for the application service layer network.

Abstract: An exemplary edge compute orchestration system that is communicatively coupled with a set of edge compute nodes in a communication network receives a task assignment request generated by a user equipment (“UE”) device coupled to the network. The request is associated with an edge compute task that is to be performed in furtherance of an application executing on the UE device. The system also accesses node characterization data for the set of nodes and manages a node selection policy configured to facilitate a balancing of node performance and node efficiency when assigning edge computing tasks to different nodes in the set. The system selects a node for performance of the edge compute task from the set of nodes in response to the request, based on the node characterization data, and in accordance with the selection policy. The system assigns the edge compute task to be performed by the selected node.

Abstract: Embodiments of the present disclosure pertain to systems and method for extracting data from an image. In one embodiment, a method of extracting data from an image comprises receiving, from an optical character recognition (OCR) system, OCR text in response to sending an image to the OCR system. The OCR text comprises a plurality of lines of text. Each line of text is classified as either a line item or not a line item using a machine learning algorithm, and a plurality of data fields are extracted from each line of text classified as a line item.